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09/12/2023
Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive Learning
Recently, multi-modal vision-language foundation models have gained sign...
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08/29/2023
PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer
We present PBFormer, an efficient yet powerful scene text detector that ...
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08/18/2023
ChatHaruhi: Reviving Anime Character in Reality via Large Language Model
Role-playing chatbots built on large language models have drawn interest...
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08/17/2023
Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach
Text recognition methods are gaining rapid development. Some advanced te...
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08/15/2023
Teach LLMs to Personalize – An Approach inspired by Writing Education
Personalized text generation is an emerging research area that has attra...
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07/14/2023
EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus
Large language models (LLMs) have achieved significant performance in ma...
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06/20/2023
Globally optimal solutions to a class of fractional optimization problems based on proximity gradient algorithm
We establish globally optimal solutions to a class of fractional optimiz...
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06/11/2023
RestGPT: Connecting Large Language Models with Real-World Applications via RESTful APIs
Tool-augmented large language models (LLMs) have achieved remarkable pro...
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04/18/2023
Understand Data Preprocessing for Effective End-to-End Training of Deep Neural Networks
In this paper, we primarily focus on understanding the data preprocessin...
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04/12/2023
Few-shot Class-incremental Learning for Cross-domain Disease Classification
The ability to incrementally learn new classes from limited samples is c...
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03/15/2023
A Comprehensive Study on Post-Training Quantization for Large Language Models
Post-training quantization () had been recently shown as a compromising ...
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01/27/2023
Understanding INT4 Quantization for Transformer Models: Latency Speedup, Composability, and Failure Cases
Improving the deployment efficiency of transformer-based language models...
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01/21/2023
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
With the growing model size, deep neural networks (DNN) are increasingly...
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12/18/2022
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models
Large crossed mixed effects models with imbalanced structures and missin...
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11/27/2022
Radial Neighbors for Provably Accurate Scalable Approximations of Gaussian Processes
In geostatistical problems with massive sample size, Gaussian processes ...
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11/24/2022
Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates
We consider performing simulation experiments in the presence of covaria...
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11/24/2022
Iterative Data Refinement for Self-Supervised MR Image Reconstruction
Magnetic Resonance Imaging (MRI) has become an important technique in th...
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11/17/2022
Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers
Large-scale transformer models have become the de-facto architectures fo...
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11/16/2022
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation
Volumetric magnetic resonance (MR) image segmentation plays an important...
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11/16/2022
Uncertainty-Aware Multi-Parametric Magnetic Resonance Image Information Fusion for 3D Object Segmentation
Multi-parametric magnetic resonance (MR) imaging is an indispensable too...
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11/15/2022
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans
Brain tumor segmentation based on multi-modal magnetic resonance imaging...
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11/15/2022
Adaptive PromptNet For Auxiliary Glioma Diagnosis without Contrast-Enhanced MRI
Multi-contrast magnetic resonance imaging (MRI)-based automatic auxiliar...
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10/22/2022
Performance Analysis of the Full-Duplex Communicating-Radar Convergence System
This paper aims to explore the feasibility of the spectrum sharing betwe...
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08/26/2022
From WSI-level to Patch-level: Structure Prior Guided Binuclear Cell Fine-grained Detection
Accurately and quickly binuclear cell (BC) detection plays a significant...
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08/08/2022
SelfCoLearn: Self-supervised collaborative learning for accelerating dynamic MR imaging
Lately, deep learning has been extensively investigated for accelerating...
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07/29/2022
BiFeat: Supercharge GNN Training via Graph Feature Quantization
Graph Neural Networks (GNNs) is a promising approach for applications wi...
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07/21/2022
Fixed-domain Posterior Contraction Rates for Spatial Gaussian Process Model with Nugget
Spatial Gaussian process regression models typically contain finite dime...
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07/01/2022
Rethinking Query-Key Pairwise Interactions in Vision Transformers
Vision Transformers have achieved state-of-the-art performance in many v...
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06/30/2022
DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale
The past several years have witnessed the success of transformer-based m...
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06/20/2022
SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes
Ghosting artifacts, motion blur, and low fidelity in highlight are the m...
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03/18/2022
Rethinking the optimization process for self-supervised model-driven MRI reconstruction
Recovering high-quality images from undersampled measurements is critica...
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02/15/2022
Secure Beamforming Design for Rate-Splitting Multiple Access in Multi-antenna Broadcast Channel with Confidential Messages
As physical layer security evolves to multi-user systems, multi-user int...
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02/03/2022
PARCEL: Physics-based unsupervised contrastive representation learning for parallel MR imaging
With the successful application of deep learning in magnetic resonance i...
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01/20/2022
Weighted Sum-Rate Maximization for Rate-Splitting Multiple Access Based Secure Communication
As investigations on physical layer security evolve from point-to-point ...
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01/08/2022
Expert Knowledge-guided Geometric Representation Learning for Magnetic Resonance Imaging-based Glioma Grading
Radiomics and deep learning have shown high popularity in automatic glio...
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01/04/2022
A Statistical Approach to Estimating Adsorption-Isotherm Parameters in Gradient-Elution Preparative Liquid Chromatography
Determining the adsorption isotherms is an issue of significant importan...
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09/26/2021
A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
Radiation therapy (RT) is widely employed in the clinic for the treatmen...
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09/26/2021
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Recent studies have witnessed the effectiveness of 3D convolutions on se...
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09/26/2021
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
Image reconstruction from undersampled k-space data plays an important r...
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08/19/2021
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
Lane detection plays a key role in autonomous driving. While car cameras...
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05/17/2021
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
Image denoising is one of the most critical problems in mobile photo pro...
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04/21/2021
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
This paper reviews the first NTIRE challenge on quality enhancement of c...
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04/16/2021
LAMPRET: Layout-Aware Multimodal PreTraining for Document Understanding
Document layout comprises both structural and visual (eg. font-sizes) in...
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03/13/2021
Supervised Learning in the Presence of Noise: Application in ICD-10 Code Classification
ICD coding is the international standard for capturing and reporting hea...
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12/30/2020
Robustness Testing of Language Understanding in Dialog Systems
Most language understanding models in dialog systems are trained on a sm...
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12/09/2020
AIDE: Annotation-efficient deep learning for automatic medical image segmentation
Accurate image segmentation is crucial for medical imaging applications....
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10/05/2020
Bayesian Fixed-domain Asymptotics: Bernstein-von Mises Theorem for Covariance Parameters in a Gaussian Process Model
Gaussian process models typically contain finite dimensional parameters ...
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10/02/2020
Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach
Search engines often follow a two-phase paradigm where in the first stag...
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08/20/2020
Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions
Computer vision (CV) has achieved great success in interpreting semantic...
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08/05/2020
